Quantum computing explained: No1 tech trend for future IT industry

On top of technology trends, quantum computing explained an explode evolution with a conventional computer. It would be the future source of technology evolution.

The concept of Quantum computing needs a deep background in math to explain. Indeed, Quantum computing technology is involved in approaching the next gent of supercomputers. Currently, two popular quantum computing companies taking deep practices of quantum computing are Google and IBM. With the desire to revolutionize communication and machine learning, Google announced their technology achievement related to quantum supremacy impressing other tech giants.  

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Cybersecurity ecosystem: Breaking the current standard

Since the world operates as a huge machine, cybersecurity ecosystem or security ecosystem are extremely invested in protecting users’ benefit against cyberattacks.

The consideration of cybersecurity and cyber threats are taken into account when severe malware attacks targeted company systems these days. 2020 cybersecurity reported that over 18,000 businesses and even government departments faced infiltration by hackers in the US alone.

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Practical solutions in solving Data Integration Challenges

The development of big data and blockchain give birth to data integration challenges. With tremendous data generated daily, companies need solutions to tackle it.   

The modern world is the world of sharing and connecting that the root of this concept refers to the capacity to freely sharing their media or data. Whereas most of those shared data is not follow the same format, it is seemingly impossible to consolidate them. Additionally, there is no official standard for data collections that companies currently leverage their custom software system in storing and processing data. Accordingly, to data integration, those companies need to scarify their secret. Obviously, there is limited form willing to do it.

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What function should a Self-service Ordering Kiosk have?

Do you know the meaning of fast-food restaurant like KFC, Lotteria? 

Yes, correct, this is the place where people can quickly order their food, quickly finish their meal or even take it away, the most important thing is “Quick Service”. That’s why the fast-food restaurant is the choice of many people around the world. However nowadays, you can see in many fast-food restaurants, people have to wait for a long time with a long queue before ordering their food. In order to improve service quality and follow the real meaning of a fast-food restaurant, a lot of restaurants used self-service software development. Let’ see what it is and how can it be applied to the development of the food and beverage business.

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AI and Big Data trends of using in F&B Companies nowadays

Mentioning Affiliate Intelligent and Big Data, people think about 4.0 Technology, which is applied from life to business. In each section, these will support in different ways, more details using their advantages to boosting business or simple our life. This is the same in F&B business, and this blog will show you some trends to implement these two in Food and Beverage nowadays.

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Three data signals travel marketers need to examine

Digital ad dollars and travel statistics aside, the travel industry could be doing a lot more to maximize its bottom line. Given the data, technology and systems that are in place, this can be achieved through a shift in attention.

NB: This is a viewpoint by Nancy Hall, senior vice president at Conversant.

There’s no denying size and scale. In fact, according to projections from eMarketer, the US travel industry laid out $5.69 billion in digital media spend in 2016. That number is projected to climb to a whopping $8.28 billion by 2020. Airlines for America estimates that an unprecedented 145 million travelers took flight in March and April this year.

So where is the travel industry falling short? Loyalty.

According to a study from the Center of Hospitality Research at Cornell University, hotel chains reap an average of 50 percent more revenue from customers who belong to their loyalty programs than from those who do not.
Why, then, do the hotels I stay at – where I am supposedly a loyalty member – greet and interact with me as if I were a stranger? Shouldn’t my loyalty be recognized?

More often than not, this happens because of companies which mismanage consumer data by not integrating that data across their entire organization. If you’re a brand marketer who wants to maintain a positive reputation and increase the value of your loyalty program, data needs to be an integral part of how you connect to and with your customers.

To navigate through the throngs of overwhelming data and maintain customer loyalty, here are three key signals to look for in your data that will help you talk to your consumers more effectively.

Firstly, you’ll want to identify users that arrive at your site.

Are they loyalty members or new prospects? Next you need to examine their site interactions. Not only should you be concerned with who’s visiting your site but also you should pay close attention to which area of the site they spend most of their time.

For example, if users are spending their time on specific property sites in Miami, you can easily tell that they have an upcoming trip to Miami, and there’s an opportunity to let them know about your relevant offers for that particular destination.

Conversely, if they are spending a fair amount of time looking for fun activities at your facility, this is your chance to upsell them during the post-booking phase based on the unique activities and/or excursions your hotel offers.

Another key data signal is location.

If you know, for example, that over the past year a user has booked flights out of New York and to San Francisco, then you can utilize that data to determine where their origin city is and which destination they’re traveling to, and whether the trip is for business or pleasure. You can also use this data to update their loyalty profiles. You can then provide them with local offers, personal or business, depending on how those locations align.

Understanding the distinction between customers’ geo-location and their home base is crucial to accurately identify contextual messaging. You don’t want to be a brand that sends hotel offers to someone in their home town.

Finally, you’ll want to pay close attention to the devices a consumer uses during certain steps of the travel booking process.

It’s important to target them most effectively in that ‘let’s book it’ moment. If someone is researching travel plans on a mobile device, for example, then that’s the correct device to target to compel them to convert – same if it’s a desktop computer on which they’re planning. Some customers may also use a combination of the two, so you’ll need to be cognizant of which device they use to actually book the trip.

Not surprisingly, more people are beginning to book entire trips in-app on their mobile devices, so marketers need to be ready to serve messages that connect with consumers across all devices. These efforts can be appended by messages shared through their loyalty account, further strengthening those relationships.

Travel marketers easily find themselves awash in a sea of data. While they may sometimes feel like they’re drowning in it, understanding how to separate the most impactful data signals from the data signals that create more noise, is the key to success.

You need to know who your potential clients are – not only their habits and what they like and dislike – and where they’re most likely to engage with your brand. Do they book in-app or on a desktop?

So the next time one of your loyal customers comes into your hotel or visits your website, will you be prepared to treat them as individuals, or will you treat them like just another number?

NB1: This is a viewpoint by Nancy Hall, senior vice president at Conversant.
NB2: Image by Bigstock.

Time to connect Big Data with hotel visuals

Today’s travelers are starting to expect a personalized experience throughout all stages of travel – something that the emergence of “big data” is helping to lead.

Not only is there some degree of expectation, but apparently 74% of consumers feel frustrated when website content is not personalized.
This shows us that in the evolving world of travel marketing, big data must be utilized in order to please (and convert) our target audience.

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